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Hiroshima J Med Sci. 2001 Mar;50(1):9-16.

An international data analysis on the level of maternal and child health in relation to socioeconomic factors.

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  • 1Institute of Health Sciences, Faculty of Medicine, Hiroshima University, Kasumi, Japan.

Abstract

International data on health and socioeconomic factors were analyzed to understand the trends and the determinants of maternal and infant mortality in the late years. Multivariate analyses were carried out to summarize the structure of the data. Multiple regression analyses were also carried out with these two mortality rates as dependent variables. The range of independent variables included health resource availability, immunization, GNP, illiteracy rates, distribution in working area, the indicators of living standards such as percentage of telephone lines and television sets per capita and the percentages of working children, population with access to safe water and sanitation, people living in urban areas, among others. In the preliminary analysis the indicators of living standards appeared highly correlated to maternal and infant mortality. Working area (industrial or agricultural) showed also an important correlation. In factor analysis indirect variables (economic and living condition) were summarized into two factors. Two regression analyses were executed. In the first the variables were used directly, while factors obtained by the factor analysis were used in the second. The second analysis confirmed the previous analysis: fertility rate, immunization and urbanization appeared as determinants of maternal mortality. Birth rate, percentage of females working in agriculture and total illiteracy appeared as determinants of infant mortality. The factors extracted in the factor analysis made a significant contribution to the second regression analysis. We concluded: 1) The factors extracted by factor analyses from indirect variables had high explanatory ability on infant mortality rates, 2) The presence of immunization together with birth rate and fertility rate in the regression models pointed out the importance of investing in birth rate reduction and disease prevention methods.

PMID:
11314858
[PubMed - indexed for MEDLINE]
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